Evidence map›Paper›PMID 18786274›Full record

ArticleBMC bioinformatics2008

Computational detection of significant variation in binding affinity across two sets of sequences with application to the analysis of replication origins in yeast.

Uri Keich, Hong Gao, Jeffrey S Garretson, Anand Bhaskar, Ivan Liachko, Justin Donato, Bik K Tye

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 34% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Uri KeichDepartment of Computer Science, Cornell University, Ithaca, NY 14853, USA. keich@cs.cornell.edu
Hong Gao
Jeffrey S Garretson
Anand Bhaskar
Ivan Liachko
Justin Donato
Bik K Tye
Cornell University · USUniversity of Wisconsin–Madison · US

Funding

Regulator of DNA Replication & Gene Expression in YeastR01GM072557 · NIGMS · CORNELL UNIVERSITY · PI TYE, BIK-KWOON · 2006 to 2009
$1.2M
Computer cluster for computational biologyS10RR020889 · NCRR · CORNELL UNIVERSITY ITHACA · PI ELBER, RON · 2005 to 2005
$500k
NCRR NIH HHS 1S10RR020889NCRR NIH HHS S10 RR020889NIGMS NIH HHS GM072557NIGMS NIH HHS R01 GM072557
6 · The paper itself

Abstract

backgroundIn analyzing the stability of DNA replication origins in Saccharomyces cerevisiae we faced the question whether one set of sequences is significantly enriched in the number and/or the quality of the matches of a particular position weight matrix relative to another set.

resultsWe present SADMAMA, a computational solution to a address this problem. SADMAMA implements two types of statistical tests to answer this question: one type is based on simplified models, while the other relies on bootstrapping, and as such might be preferable to users who are averse to such models. The bootstrap approach incorporates a novel "site-protected" resampling procedure which solves a problem we identify with naive resampling.

conclusionSADMAMA's utility is demonstrated here by offering a plausible explanation to the differential ARS activity observed in our previous mcm1-1 mutant experiments 1, by suggesting the relevance of multiple weak ACS matches to efficient replication origin function in Saccharomyces cerevisiae, and by suggesting an explanation to the observed negative effect FKH2 has on chromatin silencing 2. SADMAMA is available for download from http://www.cs.cornell.edu/~keich/.

Indexed as

AlgorithmsBase SequenceBinding SitesComputer SimulationData Interpretation, StatisticalDNA, FungalGenetic VariationModels, GeneticMolecular Sequence DataProtein BindingReplication OriginSaccharomyces cerevisiaeSequence AlignmentSequence Analysis, DNADNA, Fungal

Identifiers

PMID18786274
PMCPMC2566582
OpenAlexW1997280517

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.